Tweak to Technique Could Bolster Disease Detection

A team of Stanford researchers, led by Ron Davis, PhD, director of the Stanford Genome Technology Center, has developed a technique that they hope could more precisely detect diseases or disorders such as cancer or a heart attack.

The technique is an improved method to detect some biomarkers — protein signals in blood or tissues that flag unhealthy or diseased cells. If the biomarker of interest is present, a circle is created that includes specific proteins called antibodies that bind only to the biomarker and specialized DNA sequences. If the biomarker isn’t there, no circle forms.

The technique, a type of assay, is based on an existing method called a proximity ligation assay, or PLA, which converts the biomarker into a DNA sequence. Davis’ assay, called circular-PLA, uses additional DNA molecules to generate a circle, a step that enhances the accuracy of the approach.

“In order for the detectable circle to form, the DNA sequences have to be perfect matches with each other,” says Roxana Jalili, PhD, postdoctoral scholar in Davis’ lab. “So, if there’s no biomarker, or something incorrectly binds to the biomarker, the DNA sequences won’t match, and the circle won’t form.”

“We introduce an extra proofreading step,” explained Henrik Persson, PhD, life science researcher in Davis’ lab. The extra sequence makes it harder for the parts to line up incorrectly to generate the detectable signal, or circle.

The extra stringency is particularly important because existing tests yield too many false positives and false negatives, Davis told me.

“There’s too much complacency with the existing detection method used in clinics,” Davis said. “I think the medical community needs to push back and just not accept it.”

Davis sees potential for his technique to help detect biomarkers of diseases with high rates of false positives and negatives, such as HPV or Lyme disease. He also notes that the ability to accurately detect molecules has many potential applications beyond medicine, such as the identification of mold in a building.

Davis said he hopes clinics and researchers will raise their expectations of biomarker detection methods. “People tolerate the current method because they think, ‘Well this is the technology, what are we going to do?’” he says. “But now we actually can do something about it.”

This article has been republished from materials provided by Stanford Medicine. Note: material may have been edited for length and content. For further information, please contact the cited source.